Our definition says that leaders are, on average, more influential than
followers. As a consequence of this asymmetry, a follower's
behavior is affected by the leader's, but there is a time
delay. To determine the degree of causal influence between random variables
quantitative measures have been introduced from information theory, such as
time-delayed mutual information and transfer (conditional) entropy. As they
make no assumption about the functional relationship between variables the
latter improve on the more-commonly used measures of time-delayed correlation
[1]} and Granger causality [2]}, which can capture
only linear functional relationships.
